Methodology

Impact Models

Understanding the biodiversity impact models available in Darwin

Impact Models

Darwin offers multiple impact models to translate environmental pressures into biodiversity impacts. Each model has different strengths and is suited to different assessment needs.

Available Models

Model	Full Name	Primary Focus	Output Unit
ReCiPe Species	ReCiPe 2016 Endpoint	Species extinction risk	PDF.m².yr
ReCiPe PDF	ReCiPe 2016 Endpoint (PDF)	Potentially Disappeared Fraction	PDF.m².yr
Impact World+	IMPACT World+	Multi-indicator approach	PDF.m².yr
Impact World+ LU	IMPACT World+ (Land Use)	Land use specific	PDF.m².yr
GLOBIO	GLOBIO 4	Global biodiversity model	MSA.km²
GLOBIO Extended	GLOBIO 4 Extended	Enhanced GLOBIO	MSA.km²

Model Selection

Choose your impact model when creating a project. Consider:

Factor	Consideration
Assessment scope	Company-wide vs. product-specific
Key pressures	Land use vs. pollution focus
Reporting needs	Which frameworks you're reporting to
Data availability	What data you have available

ReCiPe 2016

Overview

ReCiPe is a widely-used Life Cycle Impact Assessment (LCIA) method developed by RIVM, Radboud University, and PRé Consultants.

Key Features

Comprehensive coverage: All major environmental pressures
Species focus: Endpoint results in species-years lost
Global scope: Applicable worldwide
Well-documented: Extensive scientific literature

ReCiPe Species vs ReCiPe PDF

Aspect	ReCiPe Species	ReCiPe PDF
Focus	Species extinction risk	Habitat loss fraction
Unit	Species.yr	PDF.m².yr
Best for	Overall biodiversity impact	Land-focused assessments

ReCiPe Species is the default model and is recommended for most assessments as it provides a balanced view of all pressure types.

IMPACT World+

Overview

IMPACT World+ is a globally regionalized life cycle impact assessment method that provides spatially-differentiated characterization factors.

Key Features

Regionalization: Impacts vary by geography
Multiple indicators: Comprehensive pressure coverage
Recent data: Updated characterization factors
Land use detail: Specific land use types

Land Use Variant (IW+ LU)

The Land Use variant provides enhanced characterization for:

Land occupation (different ecosystem types)
Land transformation (conversion impacts)
Ecosystem quality changes

Use Impact World+ LU when your assessment has significant land use components, such as agricultural commodities or real estate.

GLOBIO

Overview

GLOBIO (Global Biodiversity Model for Policy Support) is a model developed by PBL Netherlands that estimates Mean Species Abundance (MSA) based on human pressures.

Key Features

MSA metric: Mean Species Abundance relative to pristine state
Policy focus: Designed for policy evaluation
Pressure-response: Clear relationships between pressures and impacts
Spatial: Gridded global coverage

GLOBIO vs GLOBIO Extended

Aspect	GLOBIO	GLOBIO Extended
Pressures	Core pressures	Additional pressures included
Resolution	Standard	Higher resolution
Indicators	MSA only	Additional biodiversity metrics

When to Use GLOBIO

GLOBIO is particularly useful for:

Landscape-level assessments
Policy scenario analysis
Spatial biodiversity mapping
Footprint communication (MSA is intuitive)

Understanding Output Units

PDF.m².yr

Potentially Disappeared Fraction of species × Area × Time

Represents the fraction of species potentially lost
Multiplied by the area affected
Over a time period (usually one year)

Interpretation: A value of 100 PDF.m².yr means an impact equivalent to completely eliminating biodiversity from 100 m² for one year.

MSA.km²

Mean Species Abundance × Area

MSA ranges from 0 (no species) to 1 (pristine)
Multiplied by the area affected

Interpretation: A loss of 1 MSA.km² means reducing the MSA by 1 (from pristine to none) across 1 km², or reducing MSA by 0.5 across 2 km².

Comparing Models

Different models may give different absolute values for the same activity. However:

Rankings are generally consistent: Higher-impact activities score higher across models
Relative comparisons are valid: Comparing scenarios within the same model is reliable
Trend analysis works: Tracking change over time is meaningful

Avoid comparing absolute values between different impact models. The units and methodologies differ significantly.